使用by.
by(iris, iris$Species, \(x) summary(lm(Petal.Length ~ Sepal.Length, x)))
# iris$Species: setosa
#
# Call:
# lm(formula = Petal.Length ~ Sepal.Length, data = x)
#
# Residuals:
# Min 1Q Median 3Q Max
# -0.40856 -0.08027 -0.00856 0.11708 0.46512
#
# Coefficients:
# Estimate Std. Error t value Pr(>|t|)
# (Intercept) 0.80305 0.34388 2.335 0.0238 *
# Sepal.Length 0.13163 0.06853 1.921 0.0607 .
# ---
# Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
#
# Residual standard error: 0.1691 on 48 degrees of freedom
# Multiple R-squared: 0.07138, Adjusted R-squared: 0.05204
# F-statistic: 3.69 on 1 and 48 DF, p-value: 0.0607
#
# ---------------------------------------------------------
# iris$Species: versicolor
#
# Call:
# lm(formula = Petal.Length ~ Sepal.Length, data = x)
#
# Residuals:
# Min 1Q Median 3Q Max
# -0.68611 -0.22827 -0.04123 0.19458 0.79607
#
# Coefficients:
# Estimate Std. Error t value Pr(>|t|)
# (Intercept) 0.18512 0.51421 0.360 0.72
# Sepal.Length 0.68647 0.08631 7.954 2.59e-10 ***
# ---
# Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
#
# Residual standard error: 0.3118 on 48 degrees of freedom
# Multiple R-squared: 0.5686, Adjusted R-squared: 0.5596
# F-statistic: 63.26 on 1 and 48 DF, p-value: 2.586e-10
#
# ---------------------------------------------------------
# iris$Species: virginica
#
# Call:
# lm(formula = Petal.Length ~ Sepal.Length, data = x)
#
# Residuals:
# Min 1Q Median 3Q Max
# -0.68603 -0.21104 0.06399 0.18901 0.66402
#
# Coefficients:
# Estimate Std. Error t value Pr(>|t|)
# (Intercept) 0.61047 0.41711 1.464 0.15
# Sepal.Length 0.75008 0.06303 11.901 6.3e-16 ***
# ---
# Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
#
# Residual standard error: 0.2805 on 48 degrees of freedom
# Multiple R-squared: 0.7469, Adjusted R-squared: 0.7416
# F-statistic: 141.6 on 1 and 48 DF, p-value: 6.298e-16
编辑
为了详细说明我的 comments ，我们可以非常容易地提取所需的值
by(iris, iris$Species, \(x) lm(Petal.Length ~ Sepal.Length, x)) |>
lapply(\(x) {
with(summary(x), c(r2=r.squared, f=fstatistic,
p=do.call(pf, c(as.list(unname(fstatistic)), lower.tail=FALSE))))
}) |> do.call(what=rbind)
# r2 f.value f.numdf f.dendf p
# setosa 0.07138289 3.689765 1 48 6.069778e-02
# versicolor 0.56858983 63.263024 1 48 2.586190e-10
# virginica 0.74688439 141.636664 1 48 6.297786e-16